A. Technical Field
The present invention pertains generally to image processing, and relates more particularly to model-based image processing.
B. Background of the Invention
Emerging communications trends point to streaming video as a new form of content delivery. These systems are implemented over wired systems, such as cable and wireless networks, such as wireless Internet and cell phones. These communications systems require sophisticated methods of compression and error-resilience encoding to enable communications across bandwidth-limited and noisy delivery channels. Additionally, the transmitted video data must be of high enough quality to ensure a satisfactory end-user experience.
Traditionally, video compression makes use of temporal and spatial coherence to reduce the information required to represent an image. In many communications systems, the communication channel is characterized by a probabilistic model, which describes the capacity or fidelity of the channel.
In many communication scenarios, such as online conferencing, human face images comprise a large percentage of the visual data. A good understanding of human face images is important in order to achieve good performance on such applications such as, for example, enhancing the display quality or recovering image errors due to missing data or compression effects in the video streams.